Network Analysis

GEOG 40323

March 6, 2018

Distance in GIS

  • Review: how can distance be measured in a GIS context?

Types of distance in GIS

  • Euclidean (planar) distance
  • Manhattan distance
  • Geodesic distance
  • Network distance

Euclidean vs. Manhattan distance

Source: Wikipedia

Geodesic distance

Source: Esri

Distance in urban/business analysis

Network distance

  • Core principle: determination of shortest distance between two points along a network
  • Based on topological relationships between features

‘Cost’ and network analysis

Source: Bolstad, GIS Fundamentals

The Dijkstra algorithm

Source: Bolstad, GIS Fundamentals

Linear referencing

  • A type of alternative datum for determining relative locations
  • Linear referencing system: features stored with reference to line features (e.g. I-35W, mile 15.6); can be used instead of x, y coordinates

Topology

Source: Bolstad, GIS Fundamentals

Other types of network analysis

  • Geometric networks

Source: Esri

Components of a road network

  • A linear reference (generally, a streets dataset)
  • Some way to calculate a cost attribute along the network, e.g.;
  • Distance: length of line segment
  • Time: impedance to travel
  • Information about characteristics of a road network

Time as a cost attribute

  • How to calculate? Must have some ancillary information about travel speeds along roads
  • Example: speed limit information; traffic profiles
  • Basic formula: \(time = rate / distance\)
  • Gets more complicated with traffic

Traffic in network analysis

Source: Esri

Traffic in ArcGIS

Network analysis and logistics

Video on UPS’s ORION system

Applications of network analysis

  • Vehicle routing
  • Service area (drive-time) analysis
  • Closest facility analysis
  • Location-allocation modeling
  • Advanced business analytics

Vehicle routing

Service area analysis

  • Tutorial!

Closest facility analysis

Location-allocation modeling

Source: Esri

Gravity modeling

In a GIS context, a gravity model can be specified as:

\[P_{ij} = \dfrac{W_i/D_{ij}^\alpha}{\sum_{i=1}^{n}(W_i/D_{ij}^\alpha)}\]

Where:

\(P_{ij}\) = the probability of customer \(j\) shopping at store \(i\);

\(W_i\) = some measure of the attractiveness of each store \(i\);

\(D_{ij}\) = the distance from customer \(j\) to store \(i\);

\(\alpha\) = a distance-decay parameter

Huff model

  • Employs principles of gravity modeling to forecast customer demand, sales potential
  • Implemented in Esri’s Business Analyst for Desktop

Image source

Network analysis beyond ArcGIS

  • pgRouting: Adds routing functionality to PostgreSQL/PostGIS; can be integrated with QGIS
  • Employs OpenStreetMap data

Want to do more?

Check out the suite of Esri Network Analyst tutorials here: